Rationale: Patients with asthma were advised to avoid coronavirus disease (COVID-19) and comply with medication during the COVID-19 pandemic. Respiratory tract infection is a common cause of asthma exacerbations. There has not been evidence suggesting the link between COVID-19 and asthma exacerbation, especially in places with dramatic responses in infection control with universal masking and aggressive social distancing. Objectives: To assess the number for admissions of asthma exacerbations in January to April 2020 in Hong Kong with reference to admission in the past 5 years. Methods: Admission records of asthma exacerbations were retrieved from the Clinical Data Analysis and Reporting System. Patients aged 18 years or older with a known history of asthma admitted for asthma exacerbation were included. Log-linear was used to model count, with year and masking used as covariate and further analysis on ambient temperature and length of hospital stays. Fisher’s exact test was used to compare the mortality rate and mechanical ventilation between the periods. Admissions for myocardial infarction, ischemic stroke, and gastric ulcer were included as controls. Results: The number of admissions for asthma exacerbations significantly decreased by 53.2% (95% confidence interval [CI], 50.4–55.8%) in 2020 compared with monthly average admission in 2015–2019, with a higher magnitude of decrease compared with control diagnoses. Admissions for asthma exacerbations decreased by 2.0% (95% CI, 1.8–2.2%) with every 1°C (1.8°F) increase in temperature and by 0.8% with every 1% increase in masking (95% CI, 0.8–0.9%). Conclusions: Hospitalization number for asthma exacerbations significantly decreased in early 2020, with similar length of stay. This was observed with concomitant practice of universal masking and social distancing during the COVID-19 pandemic in Hong Kong. We proposed that universal masking and social distancing reduced respiratory viral infection, leading to fewer hospital admissions for asthma exacerbations.

Accessibility of diagnostic screening and treatment monitoring devices for respiratory diseases is critical in promoting healthcare and reducing sudden complications and mortality. Spirometry is the standard for diagnosing and monitoring several lung diseases. However, it lacks regional assessment capabilities necessary for detecting subtle regional changes in certain diseases. It also requires challenging breathing maneuvers difficult for elderlies, children, and diseased patients. Here, we actualized an affordable, portable, and self-administrable electrical impedance tomography (EIT) system for home-based lung function assessment and telemedicine. Through simultaneous EIT-spirometry trials on healthy subjects, we demonstrated that our device can predict spirometry indicators over a wide range and can provide regional mapping of these indicators. We further developed a close-to-effortless breathing paradigm and tested it by longitudinally monitoring a COVID-19 discharged subject and two healthy controls with results suggesting the paradigm can detect initial deterioration followed by recovery. Overall, the EIT system can be widely applicable for lung function screening and monitoring both at homes and clinics.

Background: Electronic health record (EHR) databases can facilitate epidemiology research into various diseases including asthma. Given the diagnostic challenges of asthma, the validity of the coding in EHR requires clarification. We aimed to assess the validity of International Classification of Diseases, 9th Revision (ICD-9) code algorithms for identifying asthma in the territory-wide electronic medical health record system of the Clinical Data Analysis and Reporting System (CDARS) in Hong Kong. Methods: Adult patients who had the diagnosis of asthma input from all public hospitals in Hong Kong and those from Queen Mary Hospital in 2011– 2020 were identified using the ICD-9 code of 493 (493.0, 493.1, 493.2, and 493.9) by CDARS. Patients’ clinical record and spirometry were reviewed by two respiratory specialists to confirm the presence of asthma in the randomly selected cases. Results: There were 43,454 patients who had the diagnostic code of asthma among all public hospitals in Hong Kong and 1852 in Queen Mary Hospital in the same period. A total of 200 cases were randomly selected and validated using medical record and spirometry review by a respiratory specialist. The overall positive predictive value (PPV) was 85.0% (95% CI 80.1− 89.9%). Conclusion: This was the first ICD-9 code validation for CDARS (EHR) in Hong Kong on asthma. Our study demonstrated that using ICD-9 code (493.0, 493.1, 493.2 and 493.9) to identify asthma can result in a PPV that was reliable to support the utility of the CDARS database for further research on asthma among the Hong Kong population.

Background: While different COVID-19 vaccines have been developed, there has been lack of data on the efficacy comparison between mRNA and inactivated whole virus vaccine among patients with chronic respiratory diseases, including asthma, chronic obstructive pulmonary disease (COPD), and bronchiectasis. Methods: This was a retrospective case control study on the efficacy of BNT162b2 (mRNA vaccine) and CoronaVac (inactivated whole virus vaccine) against COVID-19 in patients with chronic respiratory diseases. A total of 327 patients were included, with 109 patients infected with COVID-19 matched with 218 patients without COVID-19. The co-primary outcomes were vaccine effectiveness against symptomatic COVID-19, COVID-19-related hospitalization and COVID-19-related respiratory failure. Vaccine effectiveness was calculated using the formula (1-adjusted odds ratio) x 100. Results: Patients who received at least 2 doses of CoronaVac had lower risk of being hospitalized for COVID-19 and developing respiratory failure than those who did not have vaccination, with adjusted odds ratio (OR) of 0.189 (95% CI = 0.050– 0.714, p = 0.014) and 0.128 (95% CI = 0.026– 0.638, p = 0.012) respectively. Patients who received at least 2 doses of BNT162b2 had lower risk of being hospitalized for COVID-19 and developing respiratory failure than those who did not have vaccination with adjusted OR of 0.207 (95% CI = 0.043– 0.962, p = 0.050) and 0.093 (95% CI = 0.011– 0.827, p = 0.033) respectively. There was no statistically significant difference in the risks of being hospitalized for COVID-19 and developing respiratory failure between patients who received at least 2 doses of CoronaVac or BNT162b2. Conclusion: BNT162b2 and CoronaVac vaccines are effective in preventing hospitalization for COVID-19 and respiratory failure complicating COVID-19 among patients with chronic respiratory diseases. Patients with chronic respiratory diseases should be encouraged to have COVID-19 vaccination.

While molnupiravir (MOV) and nirmatrelvir–ritonavir (NMV-r) were developed for treatment of mild to moderate COVID-19 infection, there has been a lack of data on the efficacy among unvaccinated adult patients with chronic respiratory diseases, including asthma, chronic obstructive pulmonary disease (COPD) and bronchiectasis. A territory-wide retrospective cohort study was conducted in Hong Kong to investigate the efficacy of MOV and NMV-r against severe outcomes of COVID-19 in unvaccinated adult patients with chronic respiratory diseases. A total of 3267 patients were included. NMV-r was effective in preventing respiratory failure (66.6%; 95% CI, 25.6–85.0%, p = 0.007), severe respiratory failure (77.0%; 95% CI, 6.9–94.3%, p = 0.039) with statistical significance, and COVID-19 related hospitalization (43.9%; 95% CI, −1.7–69.0%, p = 0.057) and in-hospital mortality (62.7%; 95% CI, −0.6–86.2, p = 0.051) with borderline statistical significance. MOV was effective in preventing COVID-19 related severe respiratory failure (48.2%; 95% CI 0.5–73.0, p = 0.048) and in-hospital mortality (58.3%; 95% CI 22.9–77.4, p = 0.005) but not hospitalization (p = 0.16) and respiratory failure (p = 0.10). In summary, both NMV-r and MOV are effective for reducing severe outcomes in unvaccinated COVID-19 patients with chronic respiratory diseases.